Evidence map›Paper›PMID 29730990›Full record

ArticleBMC biology2018

Time-resolved transcriptome and proteome landscape of human regulatory T cell (Treg) differentiation reveals novel regulators of FOXP3.

Angelika Schmidt, Francesco Marabita, Narsis A Kiani, Catharina C Gross, Henrik J Johansson, Szabolcs Éliás, Sini Rautio, Matilda Eriksson, Sunjay Jude Fernandes, Gilad Silberberg and 8 more

Abstract read
In one paragraph

Article in BMC biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Angelika SchmidtUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden. Schmidt_Angelika@outlook.com.ORCID 0000-0002-1185-3012
Francesco MarabitaUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Narsis A KianiUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Catharina C GrossDepartment of Neurology, University Hospital Münster and University of Münster, 48149, Münster, Germany.
Henrik J JohanssonDepartment Oncology-Pathology, Cancer Proteomics Mass Spectrometry, Science for Life Laboratory, Karolinska Institutet, 17176, Stockholm, Sweden.
Szabolcs ÉliásUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Sini RautioDepartment of Computer Science, Aalto University, FI-00076, Aalto, Finland.
Matilda ErikssonUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Sunjay Jude FernandesUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Gilad SilberbergUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Ubaid UllahTurku Centre for Biotechnology, University of Turku and Åbo Akademi University, FI-20521, Turku, Finland.
Urvashi BhatiaDepartment of Neurology, University Hospital Münster and University of Münster, 48149, Münster, Germany.
Harri LähdesmäkiDepartment of Computer Science, Aalto University, FI-00076, Aalto, Finland.
Janne LehtiöDepartment Oncology-Pathology, Cancer Proteomics Mass Spectrometry, Science for Life Laboratory, Karolinska Institutet, 17176, Stockholm, Sweden.
David Gomez-CabreroUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden.
Heinz WiendlDepartment of Neurology, University Hospital Münster and University of Münster, 48149, Münster, Germany.
Riitta LahesmaaTurku Centre for Biotechnology, University of Turku and Åbo Akademi University, FI-20521, Turku, Finland. rilahes@utu.fi.
Jesper TegnérUnit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden. jesper.tegner@ki.se.

Funding

European Research Council 617393
6 · The paper itself

Abstract

backgroundRegulatory T cells (Tregs) expressing the transcription factor FOXP3 are crucial mediators of self-tolerance, preventing autoimmune diseases but possibly hampering tumor rejection. Clinical manipulation of Tregs is of great interest, and first-in-man trials of Treg transfer have achieved promising outcomes. Yet, the mechanisms governing induced Treg (iTreg) differentiation and the regulation of FOXP3 are incompletely understood.

resultsTo gain a comprehensive and unbiased molecular understanding of FOXP3 induction, we performed time-series RNA sequencing (RNA-Seq) and proteomics profiling on the same samples during human iTreg differentiation. To enable the broad analysis of universal FOXP3-inducing pathways, we used five differentiation protocols in parallel. Integrative analysis of the transcriptome and proteome confirmed involvement of specific molecular processes, as well as overlap of a novel iTreg subnetwork with known Treg regulators and autoimmunity-associated genes. Importantly, we propose 37 novel molecules putatively involved in iTreg differentiation. Their relevance was validated by a targeted shRNA screen confirming a functional role in FOXP3 induction, discriminant analyses classifying iTregs accordingly, and comparable expression in an independent novel iTreg RNA-Seq dataset.

conclusionThe data generated by this novel approach facilitates understanding of the molecular mechanisms underlying iTreg generation as well as of the concomitant changes in the transcriptome and proteome. Our results provide a reference map exploitable for future discovery of markers and drug candidates governing control of Tregs, which has important implications for the treatment of cancer, autoimmune, and inflammatory diseases.

Indexed as

Cell DifferentiationCell LineForkhead Transcription FactorsGene Expression RegulationHumansProteomeSequence Analysis, RNASignal TransductionT-Lymphocytes, RegulatoryTranscriptomeTransforming Growth Factor betaForkhead Transcription FactorsFOXP3 protein, humanProteomeTransforming Growth Factor betaData integrationFOXP3iTregProteomicsRegulatory T cellsRNA sequencing (RNA-Seq)T cell differentiationTGF-βTreg

Identifiers

PMID29730990
PMCPMC5937035

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.